Software development projects are notorious for cost overruns and schedule delays. While dozens of software cost models have been proposed, few of them seem to have any degree of consistent accuracy. One major factor contributing to this persistent and widespread problem is an inadequate understanding of the real behavior of software development processes. We believe that software development could be studied as an economic production process and that established economic theories and methods could be used to develop and validate software production and cost models. We present the results of evaluating four alternative software production models using the P-test, a statistical procedure developed specifically for testing the truth of a hypothesis in the presence of alternatives in econometric studies. We found that the truth of the widely used Cobb-Douglas type of software production and cost models (e.g., COCOMO) cannot be maintained in the presence of quadratic or translog models. Overall, the quadratic software production function is shown to be the most plausible model for representing software production processes. Limitations of this study and future directions are also discussed.